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Sr. Specialist, Technical Product Management

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Merck
Full Time position
Listed on 2026-08-29
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager, Data Scientist, Data Engineering
Salary/Wage Range or Industry Benchmark: 117000 - 184000 USD Yearly USD 117000.00 184000.00 YEAR
Job Description & How to Apply Below

Job Description

We aspire to be the premier research-intensive biopharmaceutical company. We're at the forefront of research to deliver innovative health solutions that advance the prevention and treatment of diseases in people and animals.

We are seeking a Sr. Specialist Technical Product Management with deep expertise in the drug discovery and pre-clinical research process to help build and enhance data products. Join our team to bridge the gap between scientific requirements and data-driven product development and make a significant impact on global health.

Responsibilities
  • Collaborate closely with Product, Data Science, and Engineering teams to define and develop data products tailored for drug discovery and preclinical research.
  • Gather, manage, and prioritize product requirements by engaging with scientific stakeholders to understand user problems, technical constraints, and strategic objectives.
  • Define and refine the product backlog; create actionable user stories that reflect the unique workflows and challenges of preclinical drug discovery.
  • Act as a user expert, deeply understanding the motivations, pain points, and goals of scientific users.
  • Justify and prioritize improvements to existing products, focusing on delivering measurable value to scientific research and operations.
  • Develop and maintain technical knowledge and domain expertise in drug discovery, cheminformatics, and data-driven research processes.
  • Write clear problem statements and requirements; facilitate solution design with engineering teams.
  • Serve as Product Owner on Agile teams or work closely with one to ensure scientific and data needs are met.
  • Plan, design, and conduct testing activities; compile critical training and communication content for scientific end-users.
  • Analyze data, observations, and research to generate insights that inform product strategy and decision-making.
  • Support the Product Manager in defining and executing strategy in collaboration with engineering teams for one or more data products.
  • Accept completed user stories, ensuring deliverables meet acceptance criteria and scientific requirements.
  • Act as a customer champion, articulating and advocating for the needs of scientific stakeholders.
Required
  • Bachelor’s degree in Life Sciences, Biomedical Engineering, Chemical Engineering, Computer Science, or a related field.
  • Two or more (2+) years building tools or data assets supporting scientific or data analytics workflows.
  • Three or more (3+) years working with scientific users (e.g., chemists) to define requirements for data products.
  • Experience with data analytics or data science capabilities, especially in a scientific context.
  • Experience building ERDs, logical data models, and source-target mappings for scientific data.
  • Hands-on experience or working knowledge with data management services (AWS Athena, Glue, S3, Redshift, or similar).
  • Proficiency in SQL and scientific data management.
  • Ability to translate scientific/business problems into actionable requirements and tasks.
  • Strong analytical problem-solving skills.
  • Excellent written and verbal communication skills, with the ability to engage both technical and scientific stakeholders.
  • Ability to work independently and manage multiple complex projects simultaneously.
Preferred
  • Advanced degree in a related field.
  • Direct experience in pharmaceutical drug discovery and pre‑clinical development.
  • Domain knowledge or familiarity with cheminformatics, laboratory data, and scientific workflows.
  • Knowledge of cheminformatics platforms (e.g., Pipeline Pilot, RDKit, Open Eye) and integration with data science tools.
  • Familiarity with the drug discovery processes, including key endpoints such as potency, selectivity, ADMET properties, and lead optimization strategies.
  • Familiarity with cheminformatics tools and concepts such as molecular descriptors, fingerprints, QSAR modeling, and chemical database management.
  • Experience with Machine Learning Platforms (e.g., Sagemaker, Data Bricks) in a scientific setting.
  • Experience working in Agile software development.
  • Familiarity with cloud-based software and scientific data platforms.
Required Skills

Agile Application Development, Agile Software Project…

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